# IBM Quantum Hub at the

University of Melbourne

The IBM Quantum Hub at the University of Melbourne offers a complete approach for Members to gain early entry into quantum computing with the support of deep research expertise and the global quantum community.

## A new way of thinking

Quantum computing is moving rapidly from proof-of-concept to practical applications in science and business. Developing at a breathtaking pace, we are witnessing a period of evolving interaction between researchers and application developers.

Harnessing the creativity to drive commercial applications will depend on new thinking and new software, developed in parallel with the advancing power and reliability of quantum computing hardware. Early-adopters who drive the development of quantum software in their field will benefit from a strong IP position that will be hard for fast-followers to challenge or replicate.

## Australia's only University-based IBM Quantum Hub

Led by Professor Lloyd Hollenberg in collaboration with IBM, the University of Melbourne is the sole university-based IBM Quantum Hub in Australia and New Zealand. The team has worked in quantum computing for some two decades – during this time they have created the blueprint for a full-scale silicon quantum computer and recently set a world record for quantum entanglement on IBM Quantum devices. Through the Quantum Hub, the team is at the forefront of research into practical quantum computing.

In 2018, the team launched the web-based Quantum User Interface (QUI) – a quantum computer simulation environment for software development and training the new generation of quantum programmers.

Quantum computer technology will evolve rapidly, with members of the Quantum Hub at Melbourne positioned to direct that future, working on IBM’s most powerful quantum computers to develop software and expertise for the benefit of their sector and broader society. Professor Lloyd Hollenberg

IBM Quantum is advanced quantum cloud technology – several real quantum computer devices and simulators available for use through the cloud – enabling Fortune 500 companies, startups, national research labs and academic institutions to run experiments and explore use cases.

These devices are part of the IBM Quantum roadmap, an initiative to build universal quantum computers for business and science. Find out more at ibm.com/quantum-computing.

## Foundations of quantum technology

**Quantum bits **or **qubits **are quantum mechanical systems, like the state of a single atom or even a microscopic superconducting circuit. Classical computing works with bits, and a bit can only ever be 0 or 1. Qubits can be effectively both 0 and 1 at the same time.

This quality of qubits, called quantum **superposition**, together with the related phenomenon of **entanglement**, is where the remarkable increase in computing power begins.

As the number of qubits grow, **superposition **allows the quantum computer to represent exponentially increasing sets of numbers. To get a sense of what this means, imagine putting one grain of rice on the first square of a chessboard. Now double that number on each square and by the end of the board you’ll have 92 billion tonnes of rice.

Carefully choreographed sequences of **quantum logic gates **– the **quantum software program **– manipulate **superposition **and **entanglement **across the vast array of **quantum information**, to expand computational power.

## How does IBM Quantum help research and development?

There are problems that today’s computer systems will never be able to solve, such as accurately simulating large interacting systems, or solving certain optimisation and machine learning challenges. These kinds of problems get exponentially harder as complexity grows even a little, and for problems above a certain size classical computer systems simply run out of steam.

However, quantum computers working alongside classical computers may provide solutions. See the potential near-term applications for quantum computing.

Like the early stages of the digital revolution when no one could imagine how finance or logistics – or the very rhythms of daily life, would be transformed – we can’t yet predict where quantum computing will bring the greatest advantages.

## Potential near-term applications for quantum computing

The first business use cases for quantum computing have yet to be determined. They may include, but are not limited to:

**Pharma and Materials**, untangling complex molecular and chemical interactions to discover new drugs and materials**Supply Chain and Logistics**, finding solutions for more efficient logistics and global supply chains**Financial Services**, finding new ways to model financial data and isolate risk factors to make better investments**Artificial Intelligence**, enhancing machine learning, hybrid quantum approaches to data classification.

At the Quantum Hub, staff and students are engaged in a range of research projects, spanning fundamentals of quantum information and quantum physics of IBM devices, through to applications in a number of areas.

## Research themes

*Applications of quantum computing:* traffic optimisation and routing, machine learning, materials, chemistry, finance, bioinformatics and cybersecurity. *Science of quantum computing:* large-scale entanglement, logic gate characterisation and improvement, HPC benchmarking, and quantum error mitigation.

## Quantum User Interface

The Hollenberg group has developed a sophisticated quantum computer simulation tool – the Quantum User Interface (QUI) – for use in research and teaching.

The QUI system is integrated into the following subjects:

## Recent Quantum Hub papers

*"Realization of a discrete time crystal on 57 qubits of a quantum computer"*

Philipp Frey and Stephan Rachel

Science Advances, Vol 8, Issue 9 (2022)

Featured in The Conversation and Pursuit.

"*Process Tomography on a 7-Qubit Quantum Processor via Tensor Network Contraction Path Finding"*

Aidan Dang, Gregory A. L. White, Lloyd C. L. Hollenberg, Charles D. Hill

https://arxiv.org/abs/2112.06364 (2021)

*"Chemistry beyond the Hartree-Fock limit via quantum computed moments"*

Michael A. Jones, Harish J. Vallury, Charles D. Hill, Lloyd C. L. Hollenberg

https://arxiv.org/abs/2111.08132 (2021)

*"Truncated phase-based quantum arithmetic: error propagation and resource reduction"*

G. A. L. White, C. D. Hill, L. C. L. Hollenberg

https://arxiv.org/abs/2110.00217 (2021)

*"A scalable and fast artificial neural network syndrome decoder for surface codes"*

Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman

https://arxiv.org/abs/2110.05854 (2021)

*"Diagnosing temporal quantum correlations: compressed non-Markovian calipers"*

Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg, Charles D. Hill, Kavan Modi

https://arxiv.org/abs/2107.13934 (2021)

*"Clustering and enhanced classification using a hybrid quantum autoencoder"*

Maiyuren Srikumar, Charles D. Hill, Lloyd C. L. Hollenberg

https://arxiv.org/abs/2107.11988 (2021)

*"Non-Markovian Quantum Process Tomography"*

Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg, Kavan Modi, Charles D. Hill

https://arxiv.org/abs/2106.11722 (2021)

*"Quantum Support Vector Machines for Continuum Suppression in B Meson Decays"*

Jamie Heredge, Charles Hill, Lloyd Hollenberg, Martin Sevior

https://arxiv.org/abs/2103.12257 (2021)

*"Whole-device entanglement in a 65-qubit superconducting quantum computer"*

Gary J. Mooney, Gregory A. L. White, Charles D. Hill, Lloyd C. L. Hollenberg

https://arxiv.org/abs/2102.11521 (2021)

*"Generation and verification of 27-qubit Greenberger-Horne-Zeilinger states in a superconducting quantum computer"*

Gary J. Mooney, Gregory A. L. White, Charles D. Hill, Lloyd C. L. Hollenberg

https://arxiv.org/abs/2101.08946 (2021)

*“Performance optimisation for drift-robust fidelity improvement of two-qubit gates”*

Gregory A. L. White, Charles D. Hill, Lloyd C. L. Hollenberg

Phys. Rev. Applied, 15, 014023 (2021)

*"Cost optimal gate synthesis in the Clifford hierarchy"*

Gary J. Mooney, Charles D. Hill, Lloyd C. L. Hollenberg

Quantum 5, 396 (2021).

*“Experimental non-Markovian process characterisation and control on a quantum processor”*

Gregory A. L. White, Felix A. Pollock, Charles D. Hill, Lloyd C. L. Hollenberg, Kavan Modi*Nature Communications*,** 11**, 6301 (2020)

*“Quantum computed moments correction to variational estimates”*

Harish Vallury, Michael Jones, Charles Hill and Lloyd Hollenberg

Quantum 4, 373 (2020)

*“Entanglement in a 20-Qubit Superconducting Quantum Computer”*

Gary Mooney, Charles Hill and Lloyd Hollenberg*Scientific Reports* **9, **13465 (2019)

The IBM Quantum Hub at the University of Melbourne is the only university-based Quantum Hub in Australia and New Zealand. The team has decades of combined expertise in the field of quantum computing.

## Academics

Prof. Lloyd Hollenberg (Physics) – Q Hub Director | Prof. Udaya Parampalli (Computer Science) |

Dr. Charles Hill (Mathematics and Statistics/Physics) | Dr. Thomas Quella (Mathematics and Statistics) |

Prof. Kate Smith-Miles (Mathematics and Statistics) | A. Prof. Stephan Rachel (Physics) |

Dr. Usman Muhammad (Computer Science) | Prof. Martin Sevior (Physics) |

Prof. Carsten Murawski (Finance) | Dr. Nitin Yadev (Finance) |

Dr. Eric Mascot (Physics) |

## Collaborators

Dr. Kavan Modi (Physics, Monash University) |

Dr. Joydip Ghosh (Research & Advanced Engineering, Ford Motor Company) |

Dr. Bhaskar Roy Bardhan (Research & Advanced Engineering, Ford Motor Company) |

## Researchers

Zi Chen (MSc, Physics) | Gary Mooney (PhD, Physics) |

Floyd Creevey (PhD, Physics) | Saleh Naghdi (BSc) |

Aidan Dang (PhD, Physics) | Chris Nakhl (MSc, Physics) |

Philipp Frey (PhD, Physics) | James Nelson (MSc, Mathematics) |

Oscar Glenister (MSc, Physics) | Fanzhe Qu (MSc, CIS) |

Ben Harper (MSc, Physics) | Nathan Rhodes (MSc, Physics) |

Jamie Heredge (PhD, Physics) | Maiyuren Srikumar (PhD, Physics) |

Eugene Huang (MSc, Physics) | Sarama Tonetto (PhD, Physics) |

Mingrui Jing (MSc, Physics) | Harish Vallury (PhD, Physics) |

Michael Jones (PhD, Physics) | Jedwin Villaneuva (MSc, Physics) |

John Kam (MSc, Physics) | Peiyong Wang (MSc, CIS) |

Vivek Katial (PhD, Mathematics) | Gregory White (PhD, Physics) |

Timothy Kay (MSc, Physics) | Shaobo Zhang (MSc, CIS) |